NSABP B-41: A Study of AC Followed by a Combination of Paclitaxel Plus Trastuzumab or Lapatinib or Both Given Before Surgery to Patients With Operable HER2 Positive Invasive Breast Cancer [B41_27_POST]
RNA-seq (gene expression) · human · 27 samples
- What it is
- RNA-seq (gene expression)Gene activity measured by sequencing. The summary does not mention single-cell work, so this is most likely bulk: one average per sample, the usual starting point for comparing groups.
- Organism
- Homo sapiens (human)
- Topic
- Breast cancerThis series is part of our curated briefing on it.
- Samples
- 27 samples: 27 samples, each with a distinct title — no replicated groupsGroups are read from the sample names, not from the paper. Check the list below.
- Data you can get
- A processed table (series matrix) and supplementary files from NCBI; the raw sequencing reads from ENA. Which of these hold counts depends on the study, so check the file list.
- Paper
- Prognostic value of residual disease (RD) biology and gene expression changes during the neoadjuvant treatment in patients with HER2-positive early breast cancer (EBC)Annals of oncology : official journal of the European Society for Medical Oncology · 2025
Read the full summary ↓
Direct links to NCBI and ENA, no account and no request form. Pick by what you want to do: take the small processed table to look, the supplementary files to re-analyse, or the original raw data to start over.
Processed table
The series matrix: one table of values per sample as the submitters processed it. The smallest download, and it opens in Excel or R. Start here to see what the data look like.
Supplementary files
The count tables and other files the authors uploaded. Take only the samples you need, or the whole study as GSE275065_RAW.tar (it can run to tens of gigabytes).
Raw sequencing reads
The original FASTQ files, straight from the sequencer, held at ENA. Large, and you align them yourself, so only choose this if you need to re-process the study from scratch.
What the files usually look like: For RNA-seq the counts are usually a table among the supplementary files (look for 'counts', 'expression', 'FPKM' or 'TPM' in the file name). The series matrix of a sequencing study is sometimes nearly empty.
Also filed as BioProject PRJNA1149043. Searching any of these in the dataset finder brings you back here.
Any grouping that defines a comparison lives in the sample characteristics, which GEO records separately from the titles.
How we read this: Read from 27 sample titles: 27 distinct titles with little repetition. These groups are guessed from the sample names, not taken from the paper, so check them against the sample list below before relying on them.
- GSM8464841 Primary breast tumor, RNAseq, B41_23_E9_T_S96
- GSM8464842 Primary breast tumor, RNAseq, B41_24_3B_T_S51
- GSM8464843 Primary breast tumor, RNAseq, B41_30_15_T_S52
- GSM8464844 Primary breast tumor, RNAseq, B41_79_A3_T_S41
- GSM8464845 Primary breast tumor, RNAseq, B41_84_A4_T_S63
- GSM8464846 Primary breast tumor, RNAseq, B41_105_1A_T_S87
- GSM8464847 Primary breast tumor, RNAseq, B41_130_M_T_S75
- GSM8464848 Primary breast tumor, RNAseq, B41_147_2H_T_S43
- GSM8464849 Primary breast tumor, RNAseq, B41_164_2_T_S96
- GSM8464850 Primary breast tumor, RNAseq, B41_177_A1_T_S6
- GSM8464851 Primary breast tumor, RNAseq, B41_178_J15_T_S8
- GSM8464852 Primary breast tumor, RNAseq, B41_214_C5_T_S32
- GSM8464853 Primary breast tumor, RNAseq, B41_226_B9_T_S34
- GSM8464854 Primary breast tumor, RNAseq, B41_236_A4_T_S90
- GSM8464855 Primary breast tumor, RNAseq, B41_288_D5_T_S25
- GSM8464856 Primary breast tumor, RNAseq, B41_346_A5_T_S48
- GSM8464857 Primary breast tumor, RNAseq, B41_312_A5_T_S30
- GSM8464858 Primary breast tumor, RNAseq, B41_305_1A_T_S27
- GSM8464859 Primary breast tumor, RNAseq, B41_313_C13_T_S32
- GSM8464860 Primary breast tumor, RNAseq, B41_321_1D_T_S40
- GSM8464861 Primary breast tumor, RNAseq, B41_329_A14_T_S35
- GSM8464862 Primary breast tumor, RNAseq, B41_512_A4_T_S85
- GSM8464863 Primary breast tumor, RNAseq, B41_363_1H_T_S47
- GSM8464864 Primary breast tumor, RNAseq, B41_401_B8_T_S75
- GSM8464865 Primary breast tumor, RNAseq, B41_416_3_T_S76
- GSM8464866 Primary breast tumor, RNAseq, B41_493_C40_T_S82
- GSM8464867 Primary breast tumor, RNAseq, B41_506_B2_T_S84
- GSE104193 Hypoxia-mediated translational activation of ITGB3 in breast cancer cells enhances TGF-β signalling and malignant features in vitro and in vivo 32 samples same disease briefing
- GSE104675 Role for the Transcriptional Activator ZRF1 in Breast Cancer Progression and Endocrine Resistance 6 samples same disease briefing
- GSE10885 An integromic analysis reveals that metaplastic carcinomas are distinct from basal-like tumors. 244 samples same disease briefing
- GSE10886 A Supervised Risk Predictor of Breast Cancer Based on Biological Subtypes 226 samples same disease briefing
- GSE11121 The humoral immune system has a key prognostic impact in node-negative breast cancer 200 samples same disease briefing
- GSE234519 NSABP B-41: A Study of AC Followed by a Combination of Paclitaxel Plus Trastuzumab or Lapatinib or Both Given Before Surgery to Patients With Operable HER2 Positive Invasive Breast Cancer 245 samples shares nsabp, b-41, her2, combination, trastuzumab, paclitaxel
- GSE272626 ALS molecular subtypes are a combination of cellular and pathological features learned by deep multiomics classifiers (postmortem spinal cord) 266 samples shares post, combination
- GSE308462 ALS molecular subtypes are a combination of cellular, genetic, and pathological features learned by deep multiomics classifiers (post-mortem cortex) 260 samples shares post, combination
Metadata from NCBI GEO, cached and refreshed periodically — the NCBI page above is authoritative. Downloads link straight to NCBI/ENA; nothing is proxied through BioTransfer.